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© Author(s) 2009. This work is distributed under the Creative Commons Attribution 3.0 License.

Biogeosciences

Distribution, origin and cycling of carbon in the Tana River

(Kenya): a dry season basin-scale survey from headwaters

to the delta

S. Bouillon1,2,3, G. Abril4, A. V. Borges5, F. Dehairs2, G. Govers1, H. J. Hughes6, R. Merckx1, F. J. R. Meysman2,3, J. Nyunja7, C. Osburn8, and J. J. Middelburg3,9

1Katholieke Universiteit Leuven, Dept. of Earth & Environmental Sciences, Kasteelpark Arenberg 20, 3001 Leuven, Belgium 2Dept. of Analytical and Environmental Chemistry, Vrije Universiteit Brussel, Belgium

3Netherlands Institute of Ecology, Centre for Estuarine and Marine Ecology, Yerseke, The Netherlands 4Environnements et Pal´eoenvironnements Oc´eaniques, Universit´e Bordeaux 1, France

5Unit´e d’Oc´eanographie Chimique, Universit´e de Li`ege, Belgium 6Royal Museum for Central Africa, Dept. of Geology, Tervuren, Belgium 7Kenya Wildlife Service, P.O. Box 40241-00100, Nairobi, Kenya

8Department of Marine, Earth & Atmospheric Sciences, NC State University, Raleigh, USA 9Faculty of Geosciences, Utrecht University, PO Box 80021, 3508 TA Utrecht, The Netherlands Received: 9 June 2009 – Published in Biogeosciences Discuss.: 22 June 2009

Revised: 26 October 2009 – Accepted: 27 October 2009 – Published: 5 November 2009

Abstract. The Tana River basin (TRB) is the largest in Kenya (∼120 000 km2). We conducted a survey during the dry season throughout the TRB, analyzing a broad suite of biogeochemical parameters. Biogeochemical signatures in headwater streams were highly variable. Along the mid-dle and lower river course, total suspended matter (TSM) concentrations increased more than 30-fold despite the ab-sence of tributary inputs, indicating important resuspension events of internally stored sediment. These resuspended sed-iment inputs were characterized by a lower and14C-depleted OC content, suggesting selective degradation of more recent material during sediment retention. Masinga Dam (a large reservoir on the upper river) induced a strong nutrient re-tention (∼50% for inorganic N, ∼72% for inorganic phos-phate, and ∼40% for dissolved silicate). Moreover, while DOC pools and δ13C signatures were similar above, in and below the reservoir, the POC pool in Masinga surface wa-ters was dominated by13C-depleted phytoplankton, which contributed to the riverine POC pool immediately below the dam, but rapidly disappeared further downstream, suggesting rapid remineralization of this labile C pool in the river sys-tem. Despite the generally high turbidity, the combination of relatively high oxygen saturation levels, low δ18O signatures of dissolved O2(all <+24.2‰), and the relatively low pCO2

Correspondence to: S. Bouillon (steven.bouillon@ees.kuleuven.be)

values suggest that in-stream primary production was signif-icant, even though pigment data suggest that phytoplankton makes only a minor contribution to the total POC pool in the Tana River.

1 Introduction

River systems represent the primary pathway for carbon transport from the terrestrial to the marine environment, and are thus critical in determining the quantity and composition of carbon reaching the coastal zone. A recent data compila-tion suggests a substantial transfer of ∼2 Pg C y−1from the terrestrial biome into freshwater systems, yet less than half of this is estimated to reach the ocean (Cole et al., 2007). Accordingly, a substantial amount of terrestrial C is pro-cessed or stored within freshwater systems, which are typ-ically strong net sources of CO2 to the atmosphere (Cole et al., 1994; Cole and Caraco, 2001; Duarte and Prairie, 2005). Freshwater systems thus function as biogeochemi-cal “hotspots” on the land-ocean interface (McClain et al., 2003). Due to the overwhelming evidence for a high degree of biogeochemical processing of organic matter in freshwa-ter systems (e.g., Wollheim et al., 2006; Cole et al., 2007; Battin et al., 2008), the original view of rivers as mere inac-tive conduits for organic matter and nutrients has thus signif-icantly evolved. There is evidence that millennia-old organic

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2476 S. Bouillon et al.: A dry season basin-scale survey from headwaters to the delta

matter from soils can undergo surprisingly high degree of remineralization on a time scale of weeks after entering the aquatic system (Raymond and Bauer, 2001; see also Cole and Caraco, 2001), even though a smaller pool of more re-cent material may dominate overall remineralization (May-orga et al., 2005; Holmes et al., 2008). Considering the var-ious organic matter inputs in rivers, and large differences in the potential for carbon processing and exchange (e.g. from temperate to tropical environments, presence of flood plains, etc.), carbon cycling in rivers is in reality much more complex than the “pipeline versus reactor” view (see Cole et al., 2007) on river carbon cycling suggests: various frac-tions of dissolved and particulate organic carbon (DOC and POC) are likely to have different reactivities and thus, may be modified or remineralized very differently (Mayorga et al., 2005; del Giorgio and Pace, 2008). Key factors in de-termining the overall degree of organic matter processing in river networks are the presence and extent of hydrological retention and storage events or zones such as floodplains, deposition/resuspension of suspended sediment (Meybeck and V¨or¨osmarty, 2005; Battin et al., 2008). Although the important role of freshwater systems in carbon cycling is now well recognized, current data leave us far from reach-ing well-constrained global estimates of respiration in rivers and streams (Battin et al., 2008). A better understanding of terrestrial-aquatic linkages is not only important to improve global estimates of C processing in rivers, but also funda-mental to our understanding of the impact of ongoing and fu-ture land use changes. Many tropical and subtropical catch-ment areas suffer from intensive deforestation in upland ar-eas, resulting in an increased delivery of eroded sediment to the river system. Increasing demand for energy (hydropower stations) and water resources (e.g. for irrigation schemes) has led to a proliferation in the number of dams and reservoirs, which have a large impact on the nutrient status and sediment delivery downstream (e.g., Ittekkot et al., 2000, V¨or¨orsmarty et al., 2003; Snoussi et al., 2007). As terrestrial organic mat-ter is often the dominant carbon input in river systems (Bird et al., 1994, Martinelli et al., 1999; Coynel et al., 2005), land-use changes can in some cases be rapidly reflected in river-ine carbon and nutrient pools (e.g., Bernardes et al., 2004; Raymond et al., 2008). There is a growing body of litera-ture documenting the significant changes in organic matter characteristics in estuaries and coastal areas, indicating that the output (i.e., organic matter exported to the coastal ocean) can differ substantially in quantity and quality from the in-puts (i.e., that delivered to the estuarine zone through rivers) (e.g., Abril et al., 2002; McCallister et al., 2004; Bouillon et al., 2007). A similar process can be acting in the river sys-tem itself: biogeochemical processing of carbon during its transit in river systems implies that organic matter reaching the estuarine zone is likely to be different from the inputs re-ceived from land, both in terms of quantity and quality. Im-proving our understanding of the role of rivers in global C budgets will thus require a better understanding of the link

between soil or catchment characteristics on the terrestrial side, subsequent particle transport and organic matter pro-cessing in rivers, and the ultimate C export and burial in the ocean (Masielo, 2007; Drenzek et al., 2009).

Data compilations on carbon fluxes in freshwater systems invariably indicate that the tropical regions are severely un-derrepresented, e.g. with respect to data on riverine carbon transport (Ludwig et al., 1996, see also Williams et al., 2007), carbon metabolism in lakes (Sobek et al., 2007) and rivers (Battin et al., 2008), and estuarine CO2fluxes (Borges et al., 2005). In view of the importance of the tropics in overall riverine carbon transport and global carbon cycling in gen-eral (Ludwig et al., 1996), riverine carbon transport and pro-cessing in tropical systems and their relationship to (rapidly changing) land-use patterns is an important area for future studies.

Large-scale studies on carbon processing along the flow-path of low-latitude river basins have to date been concen-trated on a very limited number of systems, e.g., the Orinoco basin, the Ganges-Brahmaputra (Aucour et al., 2006; Galy et al., 2008), rivers in Papua New Guinea (e.g., Alin et al., 2008) and in particular an extensive body of work on the Amazon river basin (e.g., Hedges et al., 1994; Richey et al., 2002; Mayorga et al., 2005; Townsend-Small et al., 2005, 2008; Johnson et al., 2006; Aufdenkampe et al., 2007). Biogeochemical characteristics in headwater streams of the Amazon are more variable than in the mainstream, reflecting regional differences in underlying geology and soil charac-teristics (Townsend-Small et al., 2005). The Andean tribu-taries are thought to be a principle source of suspended sed-iment and associated organic matter to the Amazon main-stream (see McClain and Naiman, 2008), but significant changes in organic matter characteristics have been observed. Townsend-Small et al. (2005) and Aufdenkampe et al. (2007) showed strong downstream patterns in the biogeochemical signatures of both fine and coarse POC, with e.g. highest %OC, %N and highest POC/PN ratios in the highland tribu-taries. The latter has been suggested to be related to the lower degree of remineralization in high-altitude soils, with subse-quently higher %OC and C/N ratios in soil organic matter.

In this study, we present data on various biogeochem-ical characteristics of a tropbiogeochem-ical river basin (Tana River, Kenya), along the flowpath from the high-altitude headwaters in perennial catchment areas (i.e., with discharge throughout the year), down to the lower river meandering through semi-arid plains. An important characteristic of this river system is that a long section of the lower river (>600 km) does not receive any tributary inputs during the dry season, making it an ideal system to study within-river transformation pro-cesses. Using a large suite of parameters both on particulate and dissolved carbon pools and nutrients, we present a first basin-wide view on the inputs and processing of carbon in this tropical river basin. In particular, this paper discusses the general physico-chemical characteristics of different trib-utaries in the perennial catchment areas and along the main

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39 Figure 1.

Fig. 1. Location of the Tana River basin and sampling locations. Black symbols: main Tana River; open symbols: Masinga reservoir; grey

symbols: tributaries.

Tana River, the impact of Masinga dam on nutrient and dif-ferent aquatic C pools, and the downstream trends in differ-ent C pools and their isotope composition. Studies of low-latitude river systems have so far focussed on large, humid systems, and this study is the first to present biogeochemical data at the basin scale for a tropical river in a largely semi-arid region.

2 Materials and methods 2.1 Study area

The Tana River originates in the vicinity of Mount Kenya and is the longest river system in Kenya (∼1300 km), with a catchment area of ∼120 000 km2(Kitheka et al., 2005). An average of 4 km3of freshwater are discharged annually with peak flows occurring between April and June and a shorter high flow period during November/December. The sediment discharge carried to the Tana River mouth has been esti-mated at 3.1 and 6.8 109kg yr−1 (Syvitski et al., 2005 and Kitheka et al., 2005, respectively). The three main peren-nial headwater regions are located in high-altitude regions, i.e. the Aberdare range (Nyandarua mountains), the southern and eastern slopes of Mount Kenya, and the Nyambene Hills (Fig. 1). Tributaries along the lower course between Meru National Park and and the delta (Tula Laga, Thua Laga, and Tiva Laga) only discharge during the wet season. Several

irrigation schemes along this stretch, in addition to chan-nel losses and evaporation result in a net reduction of wa-ter flow between Garissa and the coast during the dry season (Maingi and Marsh, 2002). A number of hydroelectric power dams have been constructed along the Tana River since the late 1960’s, the largest of which is Masinga Dam which be-came operational in 1981 (Maingi and Marsh, 2002). The river enters the Indian Ocean roughly midway between Ma-lindi and Lamu, near Kipini (Fig. 1), but part of the fresh-water flow branches off into a complex network of tidal creeks, savannah-like flood plains, coastal lakes and man-grove swamps known as the Tana Delta (see Bouillon et al., 2007).

Sampling took place in February 2008, during dry season (low river flow) conditions. Samples or river water were taken in the three headwater regions, along several points on the main Tana River, and on the largest of the reservoirs (Masinga) – see details in Table 1 and Fig. 1. In the Aber-dare range, 4 streams were sampled (Muringato river, Cha-nia river, Maguru river, and Karuru river upstream of the Karuru falls) at altitudes of ∼2000 m (Muringato river) and

∼3000 m (the three other rivers). The vegetation in the Aber-dares varies with altitude, with moist tropical montane forest in the lower range, gradually giving way to bamboo forests, Hagenia forest and tussock grasslands (moors) consisting of the C4 grass Andropogon amethystinus in the upper ranges. Along the southeastern slopes of Mount Kenya, 5 rivers were

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2478 S. Bouillon et al.: A dry season basin-scale survey from headwaters to the delta

Table 1. Overview of sampling locations and selected water chemistry characteristics. Note that the full data are available as an electronic

supplementary file.

Station Location Altitude Distancea T δ18O-H2O pH NO−3 NH+4 PO3−4 Si

(m) (◦C) (µM) (µM) (µM) (µM)

Aberdares

1 Muringato river 2010 18.2 −4.5 7.50 16.1 2.34 0.88 376

2 Chania river 3020 13.0 −5.0 7.72 1.9 0.23 0.55 270

3 Maguru river 3010 11.7 n.d. 7.05 3.9 0.08 0.13 164

4 Karuru, upstream of falls 2940 13.1 −4.4 7.14 3.4 0.14 0.14 165 Nyambene Hills / Meru National Park

12 Mutundu river 620 24.1 −4.3 8.51 86.5 0.98 4.60 959 13 Rojewero river 610 26.9 −4.1 8.71 106.1 0.38 3.90 829 Mount Kenya 15 Thingithu river 1500 17.5 −5.0 7.66 64.9 0.18 0.72 587 16 Mara river 1350 20.4 −5.2 7.70 15.3 0.35 0.31 365 17 Nithi river 1400 19.7 −5.6 8.19 7.0 0.63 3.65 434 18 Ruguti river 1590 21.8 −5.5 8.20 10.3 0.49 0.77 251 19 Thuchi river 1440 24.7 −4.9 8.46 10.3 1.04 0.50 250 Masinga Dam 7 Masinga reservoir 1050 29.0 −3.1 8.30 0.6 0.13 0.12 208 8 Masinga reservoir 1050 30.6 −3.2 8.26 0.7 0.11 0.12 207 9 Masinga reservoir 1050 31.8 −3.0 8.21 0.7 0.07 0.12 208 10 Masinga reservoir 1050 31.4 −3.0 8.17 0.4 0.00 0.14 209

Main Tana River

5 Sagana river, 5 km before Masinga 1110 1194 24.3 −3.5 7.76 20.6 1.39 0.50 364 6 Tana River just below Masinga 1020 1133 23.9 −3.4 7.22 9.6 0.62 0.14 215 11 Tana River between Masinga and Katse 550 1010 30.4 −3.5 7.52 18.0 0.15 0.55 244 14 Tana River at Kora NP 350 880 25.8 −3.5 8.16 18.1 0.05 1.06 289 20 Tana River, Sankuri 150 651 29.9 −3.1 8.14 17.0 0.69 2.32 309 21 Tana River, Nanigi 110 493 31.0 −2.9 8.25 17.6 0.91 2.84 307 22 Tana River, Masalani 50 260 30.1 −2.9 8.21 17.7 0.88 3.31 314 23 Tana River, Tana River primate reserve 36 198 31.1 −2.9 8.20 18.9 0.45 3.42 313 24 Tana River, Garsen 18 101 28.9 −2.7 8.16 18.6 1.38 3.55 312 25 Tana River (Matombe branch), Chalaluma 8 50 31.2 −2.9 7.82 17.7 1.20 2.85 305 aDistance in km from the Tana River mouth at Kipini, calculated using the most northern branch of the Tana in its delta. Distances for the

upper tributaries are not provided due to insufficient digital information on their exact course.

sampled roughly along the road between Meru and Embu (Thingithu, Mara, Nithi, Rugiti, and Thuchi river). These were sampled at an altitude between 1350 and 1600 m, a zone which is largely farmland. Two perennial rivers (Mutundu river and Rojewero river) originating in the Nyambene Hills were sampled in Meru National Park (NP), close to their con-fluence with the Tana River at an altitude of ∼600 m. Vegeta-tion in Meru NP varies from open to closed-canopy savanna grasslands, with narrow bands of riverine forests along the perennial tributaries and along the Tana River. The main Tana River was sampled at 10 stations ranging in altitude from 1110 m to ∼10 m above sea level, encompassing an overall transect of >1000 km. The most upstream sampling stations along the main Tana River were located ∼5 km up-stream and ∼500 m downup-stream of Masinga dam, with fur-ther sampling locations distributed along its furfur-ther course until close to the river delta. The most downstream sampling station was located near Chalaluma on the Matomba branch

of the Tana River, the Tana River braches out in this section but Matomba had the majority of discharge during the period of sampling (O. Hamerlynck and S. Duvail, personal com-munication, 2008). Below the Tana River sampling point on the border between Meru and Kora NP (i.e. over a length of

∼800 km), no tributaries delivered water to the main river during the period sampled.

4 surface water samples were taken along a transect on the Masinga reservoir (1050 m altitude) from near the dam out-flow to approximately the middle of the reservoir. Masinga is the largest of the reservoirs on Tana River (∼120 km2) and has an estimated mean water residence time of ∼3 months, suggesting a potentially large impact on the sediment, car-bon and nutrient transport further downstream. The sediment influx was found to be much larger than anticipated and a significant part of the original storage capacity has been lost, with an estimated annual sediment deposition rate of ∼10– 15 106km3y−1(Dunne and Ongweny, 1976; Walling, 1984;

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Mutua et al., 2005). According to Schneider (2000), the sed-iment trapping efficiency of the dam ranges between 75 and 98%, with most of the deposition occurring along the thalweg and little on the reservoir terraces (Saenyi, 2003). The sus-pended sediment load of the Tana River has considerably de-creased since the dam construction (Kitheka et al., 2005), al-though there is evidence that this decrease in sediment trans-port already set in earlier (Dunne, 1977). Moreover, the flow regulation has led to major changes to the downstream river ecology, including a reduction in flood events, a reduction in the river meandering rate, and a reduction in riverine forests (see Maingi and Marsh, 2002).

2.2 Sampling and analytical techniques

Surface water for field measurements of dissolved O2, pH, temperature, and salinity were taken with a 1.7 L Niskin bot-tle from ∼0.5 m below the surface. On the main Tana River, these were taken from bridges in the middle of the river wher-ever possible. Oxygen saturation level (%O2) was measured immediately after collection with a polarographic electrode (WTW Oxi-340) calibrated on saturated air, with an accu-racy of ±1%. pH was measured using a combined elec-trode (Metrohm) calibrated on the NBS (US National Bu-reau of Standards) scale, as described by Frankignoulle and Borges (2001), with a reproducibility of ±0.005 pH units. Samples for determination of total alkalinity (TA) were ob-tained by pre-filtering 100 mL of water through precom-busted Whatman GF/F filters, followed by filtration through 0.2 µm Acrodisc syringe filters, and were stored in HDPE bottles until analysis by automated electro-titration on 50 mL samples with 0.1 mol L−1HCl as titrant (reproducibility es-timated at ±2 µmol kg−1). The partial pressure of CO2 (pCO2) and total dissolved inorganic carbon (DIC) concen-trations were computed from pH and TA measurements with the thermodynamic constants described in Frankignoulle and Borges (2001). The accuracy of computed DIC and pCO2 values are estimated at ±5 µmol kg−1and ±5 ppm, respec-tively.

Water samples for the analysis of δ13CDIC and δ18O-O2 were taken from the same Niskin bottle by gently overfilling 12 mL glass headspace vials, poisoning with 20 µL of a satu-rated HgCl2solution, and gas-tight capping with a butyl rub-ber septum and aluminum cap. For the analysis of δ13CDI C,

a He headspace was created, and ∼300 µL of H3PO4 was added to convert all inorganic carbon species to CO2. Af-ter overnight equilibration, part of the headspace was in-jected into the He stream of an elemental analyser – iso-tope ratio mass spectrometer (EA-IRMS, ThermoFinnigan Flash1112 and ThermoFinnigan Delta+XL) for δ13C mea-surements. The obtained δ13C data were corrected for the isotopic equilibration between gaseous and dissolved CO2as described in Gillikin and Bouillon (2007). For δ18O-O2, a similar headspace was created, after which they were left to equilibrate for 2 h. δ18O-O2 was then measured using the

same EA-IRMS setup by monitoring m/z 32, 33, and 34 and using a molecular sieve (5 ¨A) column to separate N2 from O2. Outside air was used as the internal standard to cor-rect all δ18O data. The 0.5 mL of water removed to cre-ate the headspace for the δ18ODO analyses was used to

de-termine δ18O signatures of H2O according to Gillikin and Bouillon (2007).

Samples for CH4were collected directly from the Niskin bottle in 40 mL headspace vials, poisoned with HgCl2, and closed with a rubber septum and aluminum cap. CH4 con-centrations were determined by gas chromatography, af-ter creating a headspace with N2, as described in Abril and Iversen (2002). Dissolved CH4 concentrations were calculated using the solubility coefficient of Yamamoto et al. (1976). Samples for ammonium, nitrate, phosphate, and silicate were obtained by pre-filtration on 47 mm GFF filters and subsequent filtration on 0.2 µm Acrodisc syringe filters, preserved with HgCl2 (1 µL mL−1 sample), and analysed with automated colorimetric techniques. A subset of sam-ples for SiO2were prepared by filtration on 0.45 µm mem-brane filters to check for possible artifacts caused by the pre-filtration procedure with glassfibre filters, but no deviations in concentrations were found.

Samples for TSM were taken with sampling bottles at

∼0.5 m below the water surface, or using a bucket when sampling from bridges along the main river. These were filtered immediately in the field on weighed and pre-combusted (overnight at 450◦C) 47 mm Whatman GF/F fil-ters, which were subsequently dried. Samples for POC, PN, and δ13CPOCwere filtered on pre-combusted 25 mm What-man GF/F filters and dried. These filters were later decar-bonated with HCl fumes under partial vacuum for 4 h, re-dried and packed in Ag cups. POC, PN, and δ13CPOCwere determined on the EA-IRMS using the TCD signal of the EA to quantify POC and PN, and by monitoring m/z 44, 45, and 46 on the IRMS. Acetanilide was used as a standard for POC and PN, while sucrose (IAEA-C6) was used to calibrate the δ13CPOCdata. Reproducibility of δ13CPOCmeasurements was better than 0.2‰. Samples for DOC and δ13CDOCwere filtered as described above for nutrients, 40 mL of filtrate was preserved in glass vials with teflon-coated screw caps, by addition of 50–100 µL of H3PO4. DOC and δ13CDOC were measured with an OI-1010 TOC analyser coupled to a Thermo DeltaPlus IRMS (see St-Jean, 2003; Osburn and St-Jean, 2007). Typical reproducibility was in the order of

<5% for DOC, and ±0.2‰ for δ13CDOC. To obtain suffi-cient amounts of suspended material for surface area mea-surements, 2–5 L of surface water was taken and pressure-filtered on 140 mm membrane filters (0.45 µm) on some of the sampling sites on the main Tana River. These filters were wrapped up in cryotubes and immediately stored on liquid N2until further processing in the laboratory.

Processing of organic carbon fractions for 114C was performed at the Royal Institute for Cultural Heritage (Brussels). After acidification with H3PO4, suspended

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2480 S. Bouillon et al.: A dry season basin-scale survey from headwaters to the delta 40 Altitude (m) 0 500 1000 1500 2000 2500 3000 T A ( m m o l k g -1) 0.0 0.5 1.0 1.5 2.0 2.5 4.6 4.8 5.0 Tributaries Masinga Tana Nyambene Hills streams Figure 2.

Fig. 2. Profile of total alkalinity (TA) in headwater streams, Masinga reservoir, and along the main Tana River. Note the break in Y-axis.

matter samples were combusted in quartz tubes with oxy-gen and copper oxide. The resulting CO2was cryogenically purified in a vacuum extraction line, and graphitized and an-alyzed for14C at the Keck AMS facility (University of Cal-ifornia). For DIC, 50–100 mL samples were acidified on the vacuum line using H3PO4 and the resulting CO2was simi-larly purified and processed. All results have been corrected for isotopic fractionation according to the conventions of Stu-iver and Polach (1977).

Surface area (SA) measurements of suspended matter were made on 200–600 mg freeze-dried and homogenized samples, using multi-point BET (Braun-Emmet-Teller) ad-sorption isotherms. Measurements were made using a Quan-tachrome NOVA 3000 surface area analyser, and verified with BCR-173 (Institute for Reference Materials and Mea-surements). While organic matter is frequently removed prior to SA measurements, the data in Mayer (1994) indi-cate that this does not systematically affect SA data – hence, no further sample pretreatment was performed.

Samples for pigment analysis by HPLC were obtained by filtering a known volume of surface water on glass fibre fil-ters (0.7 µm, Whatman GF/F), immediately rolled up in cry-otubes and stored in liquid N2. Upon return to the home lab-oratory, these were stored at −80◦C until analysis. Pigments were extracted in 10 mL acetone:water (90:10), and a sub-sample separated by HPLC on a C18 reverse phase column. Calibration was performed with working standards prepared from commercially available pure compounds.

Note that all data are also available as an electronic sup-plementary file http://www.biogeosciences.net/6/2475/2009/ bg-6-2475-2009-supplement.zip.

3 Results

3.1 General physicochemical characteristics and nutri-ent concnutri-entrations

Water temperature ranged from 11.7 to 31.8◦C, with a clear altitudinal gradient (Table 1), and with higher temperatures in surface waters of Masinga reservoir (30.7±1.2◦C) com-pared to the main Tana River just upstream and downstream of the reservoir (∼24◦C). δ18O-H2O signatures were rela-tively low in the headwater streams (−5.6 to −4.1‰), and showed a gradual increase along the course of the Tana River, from −3.5‰ upstream of Masinga reservoir to ∼

−2.8‰ in the most downstream stations (Table 1). Con-sistent with the higher temperatures in Masinga reservoir, evaporation increased δ18O-H

2O signatures in its surface wa-ters (−3.1±0.1‰) compared to the Tana River upstream and downstream (−3.5 and −3.4‰, respectively). pH values in tributaries ranged between 7.05 and 8.71, with an overall in-crease at higher altitudes (Table 1). pH in surface waters of Masinga reservoir were elevated (8.24±0.06) compared to the Tana River upstream and downstream of the reservoir (7.76 and 7.22, respectively). Along the middle and lower Tana River (below 350 m), pH was fairly stable at 8.19±0.04, but decreased sharply in the most downstream sampling sta-tion in the delta (7.82).

In all stations, NO−3 was the dominant form (83–100%) of dissolved inoraganic nitrogen (DIN). NO−3 concentra-tions showed a wide range in the different tributaries (1.9– 64.9 µM) but were fairly stable along the main Tana River (17.4±2.9 µM), the only marked pattern being a reduction of

>50% between pre-and post-Masinga Dam (Table 1). Sur-face waters of Masinga reservoir were extremely depleted in both NO−3 (0.59±0.14 µM) and NH+4 (from 0.13 µM at the most upstream location to undetectable levels near the reservoir outlet). As observed for nitrate, phosphate con-centrations were highly variable in headwater streams (0.13– 4.60 µM) and highly depleted in surface waters of Masinga reservoir (0.13±0.1 µM). Along the main Tana River, how-ever, phosphate concentrations showed a very distinct (more than 20-fold) and consistent downstream increase, from 0.14 µM below Masinga to >3 µM in the downstream part of the river (Table 1). As for NO−3 and phosphate, silicate concentrations varied widely in headwater streams (164– 959 µM, with highest concentrations in streams draining the Nyambene Hills). Along the main Tana River, a major reduc-tion was observed between pre- and post-Masinga reservoir (from 364 to 215 µM, i.e. a decrease of 41%), and further downstream, silicate concentrations increased gradually but were stable at 310±4 µM in the lower part of the river (be-low 150 m). In surface waters of Masinga reservoir, silicate concentrations (208±1 µM) were markedly lower than in the inflowing water (364 µM).

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41 Altitude (m) 0 500 1000 1500 2000 2500 3000 δ 1 3C D IC ( ‰ ) -14 -12 -10 -8 -6 -4 -2 0 2 Tributaries Masinga Tana DIC (mmol kg-1) 0 1 2 3 4 5 -14 -12 -10 -8 -6 -4 -2 0 2 δ 1 3C D IC ( ‰ ) A B Figure 3.

Fig. 3. (a) Profile of δ13CDICin headwater streams, Masinga reservoir, and along the main Tana River, and (b) plot of DIC concentrations

versus δ13CDIC.

3.2 Total alkalinity, dissolved inorganic carbon,

δ13CDICand 114CDIC

Headwater streams in the Aberdare range and on the slopes of Mt. Kenya were characterised by relatively low TA and DIC levels (0.181–1.022 mmol DIC kg−1), whereas the two streams draining the Nyambene Hills showed high TA and DIC levels (2.402 and 4.831 mmol DIC kg−1, Fig. 2). With the exception of the two latter streams, there was a clear increase in TA and DIC with decreasing altitude, and DIC levels in the main Tana River increased gradually along the entire stretch of the river, from 0.997 mmol kg−1above Masinga reservoir to 1.462 mmol kg−1 in the most down-stream sampling site (Fig. 2). δ13CDIC values ranged be-tween −7.2 and −2.4‰ in the Aberdare and Mt. Kenya streams, but were markedly lower in the (high-DIC) streams draining the Nyambene hills (−11.5 to −11.2‰ Fig. 3).

δ13CDICalong the main Tana River ranged between −7.8‰ above Masinga reservoir to −10.2‰. δ13CDIC was signif-icantly higher in the surface waters of Masinga reservoir, ranging between −4.7 and −4.4‰ (Fig. 3). 114CDICwere markedly more 14C-depleted compared to 114CPOC: one sample from Thuchi River (Mt. Kenya) had a 114CDIC signature of −658‰ (i.e. ∼8600 yr), along the main Tana River the 5 available 114CDIC data range from +178‰ (i.e., modern) upstream of Masinga reservoir to −552‰ (i.e.

∼6400 yr) at the most downstream sampling site, with an overall decrease in14C (Table 2).

pCO2 in headwater streams ranged between 110 and 1017 ppm and showed no correlation with any of the other measured parameters (Fig. 4a). For the rivers on Mt. Kenya, there was a clear decreasing pattern in pCO2 along the E-W gradient. pCO2 in surface waters of Masinga reservoir were slightly under- or oversaturated (313–443 ppm) and de-creased towards the downstream part of the reservoir. Along the Tana River, pCO2 was highest in the upper reaches, i.e. above (1085) and below Masinga reservoir (3570 and

Table 2. Overview of the available 114CPOCand 114CDICdata.

n.d.: no data.

Station Location 114CPOC 114CDIC

(‰) (‰)

Mount Kenya

19 Thuchi river n.d. −658

Main Tana River

5 Sagana river, n.d. +178

5 km before Masinga Dam

6 Tana River, n.d. −198

below Masinga Dam

11 Tana River between −88 n.d. Masinga and Katse

14 Tana River at Kora −35 −364 National Park (Adamsons Falls)

20 Tana River, −72 n.d. Sankuri 21 Tana River, −100 n.d. Nanigi 22 Tana River, −89 n.d. Masalani 23 Tana River, −116 −319

Tana River primate reserve

25 Tana River −104 −552

(Matombe branch), Chalaluma

2170 ppm). Further downstream, pCO2 was relatively low and ranged typically between 500 and 660 ppm, increasing again in the delta (1543 ppm). The latter would be consistent with earlier dry season data from the freshwater tidal estuary (4390±660 ppm, see Bouillon et al., 2007).

3.3 Dissolved oxygen and δ18O-O2

Oxygen saturation levels (%O2)were generally close to or above saturation levels in most of the headwater streams (99–118%), above saturation in surface waters of Masinga reservoir (108-114%), and highly variable in the Tana River

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2482 S. Bouillon et al.: A dry season basin-scale survey from headwaters to the delta 42 Altitude (m) 0 500 1000 1500 2000 2500 3000 p C O2 ( p p m ) 0 1000 2000 3000 4000 Tributaries Masinga Tana Altitude (m) 0 500 1000 1500 2000 2500 3000 C H4 ( n M ) 0 100 200 300 400 500 600 A B Figure 4. 5

Fig. 4. Profiles of pCO2in headwater streams, Masinga reservoir, and along the main Tana River.

43 %O2 70 80 90 100 110 120 130 δ 1 8 O -O 2 ( ‰ ) 18 19 20 21 22 23 24 Tributaries Masinga Tana Figure 5.

Fig. 5. Plot of available δ18O-O2signatures versus oxygen

satura-tion levels for headwater streams, surface waters of Masinga reser-voir, and the main Tana River. Note that data from 2 stations are not included since δ18O-O2data are missing.

(41–102%, Fig. 5). In the latter, lowest %O2 was observed just below Masinga reservoir. Throughout most of the lower Tana River, oxygen levels were slightly undersaturated, but decreased markedly in the lowest sampling site in the delta (74%), consistent with the low %O2values recorded earlier in the freshwater end-member of the Tana estuary (64±5%, Bouillon et al., 2007). δ18O-O2 values were consistently lower than the value expected for equilibrium with atmo-spheric O2 (i.e., +24.2‰), and ranged between +19.0 and +23.0‰ (Fig. 5).

3.4 Methane (CH4)

CH4 concentrations (Fig. 4b) in headwater streams ranged typically between 25 and 92 nM, except for Muringato river (314 nM) and Mutundu river (410 nM). In the main Tana River, CH4 concentrations were relatively high upstream of Masinga reservoir (505 nM) but markedly lower below

the reservoir (372 nM). In the surface waters of the reser-voir itself, CH4concentrations were the lowest observed in this study (51±7 nM). Along the middle and lower course, CH4concentrations ranged between 54 and 387 nM, with the highest concentration observed in the Tana Delta (Fig. 4b). The observed CH4concentrations consistently represent high levels of oversaturation, ranging from 850 to 21 700%. 3.5 Suspended matter and aquatic organic carbon pools TSM concentrations were generally low in the perennial headwater streams (0.6–25.4 mg L−1, with one higher record of 86.2 mg L−1in Muringato river), and in surface waters of Masinga reservoir (2.3±0.3 mg L−1). Along the main Tana River, TSM concentrations varied widely, from low values of 15.2 and 12.2 mg L−1before and after Masinga reservoir, respectively, increasing steadily to 483 mg L−1 in the most downstream sampling station (Fig. 6a). POC concentrations showed a similar altitudinal pattern (Fig. 6b), although the increase was less pronounced than for TSM, resulting in a de-creasing altitudinal gradient in %POC/TSM (Fig. 7). Along the main Tana River, %POC/TSM decreased from 4.6% after Masinga reservoir to ∼1.1% in the most downstream sam-pling stations. For surface waters of Masinga reservoir, how-ever, high %POC/TSM (32.6±3.6%) diverge from this pat-tern (Fig. 7) because particulate matter there was predomi-nantly composed of phytoplankton (see below). POC/PN ra-tios in suspended matter ranged between 8.2 and 18.5. DOC concentrations ranged between 0.3 and 2.5 mg L−1, with the majority of data in a fairly narrow range between 0.6 and 1.2 mg L−1(Fig. 8a). DOC/POC ratios (Fig. 8b) were higher in high-altitude (∼3000 m) tributaries (1.9±0.2) than in the tributaries draining Mt. Kenya and Nyambene Hills at lower altitude (0.8±0.3). Along the Tana River, DOC/POC ratios declined from ∼1.6 in the vicinity of Masinga reservoir to 0.2 along the lower Tana River (Fig. 8b). DOC/POC ratios were inversely related to the logarithm of TSM concentra-tions, but with a different relationship for tributaries and the main Tana River course (Fig. 8c).

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44 Altitude (m) 0 500 1000 1500 2000 2500 3000 T S M ( m g L -1) 0 100 200 300 400 500 600 Tributaries Masinga Tana Altitude (m) 0 500 1000 1500 2000 2500 3000 P O C ( m g L -1) 0 1 2 3 4 5 6 7 A B Figure 6.

Fig. 6. Profiles of (a) total suspended matter concentrations, and (b) particulate organic carbon concentrations in headwater streams, Masinga

reservoir, and along the main Tana River.

The specific surface areas (SA) measured on 5 of the Tana River suspended matter samples from the lower river are very high (63.6–82.2 m2g−1) compared to values re-ported for coastal sediments, estuaries and rivers (typi-cally <50 m2g−1), and OC:SA ratios found here (0.16– 0.22 mg C m−2) are consequently in the lower range of those reported in the literature (e.g., Keil et al., 1997; Auf-denkampe et al., 2007). The SA values in suspended matter are also consistently higher than those observed in surface soils which ranged between 11.8 and 67.7 m2g−1(data not shown).

3.6 Carbon sources in dissolved and suspended particu-late organic carbon: stable and radiocarbon isotope signatures

δ13C signatures of suspended POC (Fig. 9a) varied between

−26.5 and −22.7‰ for the various tributaries, and between

−25.2 and −21.2‰ along the main Tana River. In sur-face waters of Masinga reservoir, δ13CPOC was markedly more depleted, with an average signature of −29.0±0.3‰.

δ13CDOCranged between −27.7 and −21.8‰ in tributaries, within a narrow range of between −24.0 and −22.7‰ along the Tana River, and in contrast to POC, did not show a marked depletion in 13C in surface waters of Masinga reservoir, with an average δ13C of −23.9±0.3‰ (Fig. 9b). Overall, δ13CDOC and δ13CPOC were clearly uncoupled, showing a relatively weak relationship (Fig. 9c). 114C data are available for a selected number of POC samples from the main Tana River and ranged between −116 and

−35‰, corresponding to an estimated age of ∼935 and 230 years. 114CPOCshowed a general decrease along the lower Tana River, which coincides with the overall decrease in %POC/TSM in suspended matter (Fig. 10).

45 Elevation (m) 0 500 1000 1500 2000 2500 3000 % P O C /T S M 0 10 20 30 40 50 Tributaries Masinga Tana Elevation (m) 0 200 400 600 800 1000 1200 % P O C /T S M 0 1 2 3 4 5 Figure 7.

Fig. 7. Profile of %POC/TSM in headwater streams, Masinga

reser-voir, and along the main Tana River. Lower panel shows enlarge-ment for data on the main Tana River.

3.7 Pigment concentrations

Chl-a concentrations averaged 0.91±0.21 µg L−1 in the streams draining Mt. Kenya, were about twice as high (1.75±0.08) in the streams draining the Nyambene Hills, and increased from ∼0.80 µg L−1 in the upper Tana River to values between 5.23 and 6.96 µg L−1 in the lower Tana

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2484 S. Bouillon et al.: A dry season basin-scale survey from headwaters to the delta 46 D O C ( m g L -1 ) 0.0 0.5 1.0 1.5 2.0 2.5 3.0 Tributaries Masinga Tana

A

Elevation (m) 0 500 1000 1500 2000 2500 3000 D O C /P O C 0.0 0.5 1.0 1.5 2.0 2.5

B

TSM (mg L-1) 0.1 1 10 100 1000 D O C /P O C 0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5 4.0 4.5 Tributaries Masinga Tana Estuary

C

Figure 8.

Fig. 8. Profiles of (a) DOC, and (b) DOC/POC ratios, and (c) plot

of DOC/POC ratios versus TSM concentrations (log scale) in head-water streams, Masinga reservoir, and along the main Tana River. In panel (c), data from the freshwater and oligohaline zone of the Tana estuary (from Bouillon et al., 2007) are included for comparison.

River (Fig. 11a, note that no pigment data are available for the streams in the Aberdare range). In Masinga reservoir, chl-a concentrations were high (3.23–5.08 µg L−1) com-pared to the Tana River before and after the reservoir. The resulting POC/chl-a ratios (Fig. 11b) were relatively high

47 δ 1 3 C P O C ( ‰ ) -30 -29 -28 -27 -26 -25 -24 -23 -22 -21 -20 Tributaries Masinga Tana Elevation (m) 0 500 1000 1500 2000 2500 3000 δ 1 3 C D O C ( ‰ ) -29 -28 -27 -26 -25 -24 -23 -22 -21 -20

A

B

δ13C DOC (‰) -30 -29 -28 -27 -26 -25 -24 -23 -22 -21 -20 δ 1 3 C P O C ( ‰ ) -30 -29 -28 -27 -26 -25 -24 -23 -22 -21 -20

C

1:1 lin e

Figure 9.

Fig. 9. Profiles of (a) δ13C signatures in POC, (b) δ13C signatures in DOC; and (c) plot of δ13C signatures of DOC versus those of POC in headwater streams, Masinga reservoir, and along the main Tana River.

in the Mt. Kenya and Nyambene Hill streams (1156±129 and 580±31, respectively), and low in the surface waters of Masinga reservoir (206±35). Along the Tana River, POC/chl-a ratios showed no clear gradient but were rela-tively high overall (570–2081, average of 934±472).

Chl-b, indicative of green algae, was detected in most sampling sites, in particular in the lower Tana River (>500 µg L−1, but <200 µg L−1in other sites). The cyanobacterial pigment

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48 %POC/TSM 0.6 0.8 1.0 1.2 1.4 1.6 1.8 2.0 2.2 2.4 ∆ 1 4 C PO C ( ‰ ) -180 -160 -140 -120 -100 -80 -60 -40 -20 0 upstream downstream Figure 10.

Fig. 10. Covariation between %POC/TSM and radiocarbon

compo-sition of POC along the main Tana River.

echinenone was only detected in Masinga reservoir (0.15– 0.29 µg L−1), and was absent in all other sites. Zeaxan-thin (another cyanobacterial marker, but which can also be present in diatoms) was more widespread, but highest con-centrations in Masinga reservoir (0.29–0.39 µg L−1, com-pared to 0–0.25 µg L−1 elsewhere). Alloxanthin, which is very specific to cryptophytes, was present in surface waters of Masinga (0.14±0.06 µg L−1) and in the Tana River sites just upstream and downstream of Masinga reservoir, but ab-sent in all other samples.

4 Discussion

4.1 General physico-chemistry and nutrient concentra-tions, and the effects of Masinga Reservoir

Given the large altitudinal gradient covered in this survey, water temperatures ranged widely from as low as 11.7◦C in

some upper headwater streams to ∼30◦C in the lower Tana

River, and high temperatures in surface waters of Masinga Reservoir (Table 1). The longer residence time in Masinga reservoir (∼3 months) induced a local increase in δ18O-H2O in its surface waters (−3.1±0.1‰, compared to −3.5 and

−3.4‰ upstream and downstream) due to evaporation. The associated primary production (see below) also increased the pH in surface waters of Masinga reservoir (8.24±0.06) com-pared to the Tana River upstream and downstream of the reservoir (7.76 and 7.22, respectively). pH also increased fur-ther down the Tana River (with an average of 8.19±0.04 be-low 350 m), but decreased sharply near the Tana delta (7.82), consistent with the lower values reported earlier in the fresh-water end of the estuary during the end of the dry season in 2004 (7.41–7.51, see Bouillon et al., 2007).

The elevated water residence time in Masinga reservoir and associated biological processes were responsible for a

49 C h l a ( µ g L -1 ) 0 1 2 3 4 5 6 7 8 Elevation (m) 0 500 1000 1500 2000 2500 3000 P O C /C h l a 0 500 1000 1500 2000 2500

A

B

Figure 11. 5

Fig. 11. Profiles of (a) chl-a, and (b) POC/chl-a ratios in headwater

streams, Masinga reservoir, and along the main Tana River. Note that no data are available for streams draining the Aberdares, but the X-axis scale is similar to that of other profile plots for easier comparison.

major reduction in DIN (Tables 1 and 3). Surface waters of Masinga reservoir were extremely depleted in both NO−3 and NH+4, and the overall relative decrease in concentrations be-tween the main inlet and the outlet of the reservoir was 53 and 55% for NO−3 and NH+4, respectively (Table 3). The re-cent review by Harrison et al. (2009) confirms the importance of reservoirs on N retention, and estimates that these systems are responsible to up to 33% of the global N removal from lentic ecosystems (i.e. lakes and reservoirs), despite their rel-atively small areal extent. As observed for DIN, dissolved phosphate was highly depleted in surface waters of Masinga reservoir, with an overall reduction in phosphate between the main inflow and outflow of the reservoir of 72% (Table 3). Along the main Tana River, however, phosphate concentra-tions strongly increased more than 20-fold downstream (Ta-ble 1). Phosphorus dynamics in aquatic systems are often to a large extent determined by interactions with suspended par-ticles. Bound P associated with sediment particles (generally through adsorption on Fe or Al oxides) reversibly exchanges with the dissolved phase (Fox, 1989; Fox et al., 1986). Major processes responsible for release of particle-bound P include

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2486 S. Bouillon et al.: A dry season basin-scale survey from headwaters to the delta

Table 3. Comparison of selected biogeochemical parameters on the

Tana River upstream and downstream of Masinga reservoir, and in surface waters of Masinga (for the latter, n=4).

above Masinga Tana River,

reservoir surface water below dam

%O2 88 111±3 41 pH 7.76 8.24±0.06 7.22 NH+4 (µM) 1.39 0.08±0.06 0.62 NO−3 (µM) 20.6 0.59±0.14 9.6 PO+4 (µM) 0.50 0.13±0.01 0.14 SiO2(µM) 364 208±1 215 TSM (mg L−1) 15.8 2.3±0.3 12.2 δ13C-POC (‰) −22.8 −29.0±0.3 −25.2 δ13C-DOC (‰) −23.7 −23.9±0.3 −23.9 DOC (mg L−1) 1.01 0.97±0.04 0.98 %POC/TSM 4.2 32.6±3.6 4.6 pCO2(ppm) 1085 378±57 3572 CH4(nM) 505 51±7 372 δ18O-DO +22.0 +19.2±0.2 n.d. δ18O-H2O −3.5 −3.1±0.1 −3.4 δ13C-DIC −7.8 −4.5±0.1 −8.9

(i) changes in the aquatic chemistry, whereby a significant fraction of particle-associated P can be released into the wa-ter column due to competition with other anions (Deborde et al., 2008 and references therein), and (ii) resuspension of sediments, likely due to reduction of Fe/Al oxides under the anoxic conditions during storage in bottom sediments (Evans et al., 2004, and references therein). The large and steady increase in phosphate observed here along the middle and lower Tana River matches very well with the concurrent in-crease in TSM concentrations (Fig. 6), which strongly sug-gests that phosphate concentrations are indeed mainly gov-erned by dynamic exchange equilibria between dissolved P and particle-associated P.

Highest dissolved silicate concentrations were found in streams draining the Nyambene Hills. The latter region is lithologically distinct from the other headwater regions in being partly dominated by Quaternary volcanic rocks rather than Precambian or Tertiary volcanic rocks (King and Chap-man, 1972), and by its distinctively higher soil carbonate equivalent (World Soil and Terrain Database, SOTER, ac-cessible through www.isric.org). This difference in parent material and the likely lower soil thickness covering it can be expected to result in higher weathering rates of Si and other elements (Heimsath et al., 1997). In line with this, the 2 streams sampled in this area also have markedly higher concentrations of K, Ca, Mg, Na (data not shown) and to-tal alkalinity (Fig. 2) than the headwater streams draining the Aberdares and Mt. Kenya.

A major reduction between pre- and post-Masinga reser-voir was also observed for silicate (from 364 to 215 µM, i.e.

a decrease of 41%, Table 3). Consistent with this large re-duction in dissolved Si, the phytoplankton composition in Masinga reservoir has been found to consist predominantly of the diatom genus Nitzschia (Uku and Mavuti, 1994). How-ever, for both silicate and phosphate the concentrations in the outflow (Table 3) were only slightly higher than in sur-face waters, whereas for both NO−3 and NH+4, the outflowing water had concentrations about ∼50% of those in the inflow-ing Tana River, i.e. much higher than in surface waters of the reservoir (Table 3). As the outflow of the reservoir is located near the bottom (Pi´esold et al., 1985), this indicates that DIN is partly regenerated in the (likely anoxic) bottom waters, while Si and phosphate are not.

4.2 Inorganic carbon and dissolved oxygen dynamics

pCO2 values in headwater streams varied widely (110– 1017 ppm; Fig. 4a) and could not be correlated to other biogeochemical characteristics. Surface waters of Masinga reservoir were slightly under- or oversaturated in CO2(pCO2 ranging from 313–443 ppm) and decreased towards the out-flow of the reservoir. Even along the main Tana River,

pCO2was relatively low, ranging typically between 500 and 660 ppm along the lower course of the river, with the excep-tion of the outflow of Masinga reservoir (<3000 ppm) and towards the tidal floodplains in the delta (1543 ppm). Mirror-ing the relatively low pCO2data, the relatively high oxygen saturation levels in the tributaries (99–119%) and low δ18 O-O2values (all <+24.2‰), suggest substantial contributions of O2produced by in situ primary production (which has the same δ18O signature as that of the water, i.e. ranging between

−5.6 and −4.1‰ for the tributaries). A clear negative cor-relation between δ18O-O2 and %O2 is evident for the data from the main Tana River and Masinga reservoir (Fig. 5), as expected based on isotope fractionation during respiration (i.e. remaining O2becomes enriched in18O) and photosyn-thetic O2inputs (which increases %O2and decreases δ18 O-O2, due to inputs of O2with a signature similar to that of the source H2O, see Guy et al. (1993)). In contrast, the data from the headwater streams do not show a clear relationship be-tween %O2and δ18O-O2(Fig. 5), suggesting that other pro-cesses besides pelagic photosynthesis and pelagic respiration are significant in influencing O2dynamics (e.g. benthic O2 consumption which is accompanied with little fractionation (Brandes and Devol, 1997). Data on %O2and δ18O-O2data can be used to estimate the ratio of primary production to res-piration (P:R) in freshwater systems (Quay et al., 1995) when steady state conditions apply, i.e., when no significant diurnal variations in %O2and δ18O-O2occur. When steady-state as-sumptions are not met, such as in highly productive shallow-water ecosystems, this approach may introduce a significant bias in estimated P:R ratios (e.g., Tobias et al., 2007), but for Masinga reservoir and the lower Tana River, we believe this approach offers a reasonable first estimate. Resulting P:R estimates range from 1.1 to 1.3 for Masinga reservoir and

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between 0.76 and 1.08 for the main Tana River. Although the assumption of steady-state conditions can not be veri-fied in the absence of data on diurnal variations, the clear negative correlation between P:R estimates and pCO2data (R2=0.89 for an inverse first order fit, data not shown) sug-gests that our approach provides a relative indication of P:R in this system. In conclusion, although direct metabolic pro-cess rates are currently unavailable for any of the sampling sites, the combination of pigment concentrations and indirect indicators of aquatic metabolism (pCO2, %O2, δ18O-O2) all suggest that in situ primary production cannot be ignored as a potential contributor to carbon sources in the system – even in the highly turbid lower Tana River.

4.3 Isotope contraints on inorganic carbon origin and cycling

Considering all sampling sites, δ13CDICwas negatively cor-related with DIC concentrations, i.e. highest DIC concentra-tions were associated with lowest δ13CDIC(Fig. 3b). High-altitude streams in the Aberdares and on Mt. Kenya had low DIC concentrations and relatively high δ13CDIC, while those draining the lower Nyambene Hills show remarkably high DIC concentrations and much lower δ13CDIC; samples from the main Tana River are intermediate between these signa-tures (Fig. 3b). A largely similar pattern was observed in the Rhˆone basin (France) by Aucour et al. (1999), where upstream (Alpine) tributaries showed lower DIC and more enriched δ13CDI C values, while lowland tributaries showed

higher DIC and lower δ13CDIC. Aucour et al. (1999) at-tributed this trend to a dominance of carbonate weathering with biogenic CO2as the DIC source in their lowland trib-utaries, while they suggested that carbonate dissolution with atmospheric CO2and/or organic/sulfuric acids dominated in the higher altitude tributaries. In our dataset, however, we found δ13CDIC to be negatively correlated with both Ca2+ and silicate concentrations in the headwater streams, and DIC concentrations are well correlated with both Ca2+and Si concentrations. Silicate weathering results in a DIC pool with a δ13C signature expected to range between −18 and

−5‰ (for C3- and C4-dominated sites, respectively), i.e., similar to that of the organic matter remineralized within the soil but taking into account additional fractionation during diffusion of CO2 into the soil water phase (see Brunet et al., 2005). A further enrichment in13C can be expected in these relatively shallow tributaries due to atmospheric ex-change (e.g., Doctor et al., 2008). Streamwater DIC from atmospheric inputs or carbonate mineral dissolution by bio-genic CO2 would result in more enriched δ13C signatures (∼-12 to −2‰), since DIC produced by carbonate dissolu-tion is composed of equal fracdissolu-tions of soil CO2 (δ13C de-pending on C3/C4 abundance, 114C variable) and carbon-ates (δ13C ∼0‰ and14C-free assuming ancient marine car-bonates). Thus, a further contrast between silicate weather-ing and carbonate weatherweather-ing can be expected in the resultweather-ing

50 δ13C (‰) -30 -25 -20 -15 -10 -5 0 ∆ 1 4 C ( ‰ ) -1000 -800 -600 -400 -200 0 200 DIC POC CO2 from in situ mineralization

(based on POC data)

silicate weathering carbonate weathering carbonates atm. CO2 Figure 12

Fig. 12. Plot of δ13C and 114C signatures in DIC observed in this study, along with representative signatures of potential DIC sources.

δ13C and 114C signatures of POC are also plotted to indicate the expected signatures for CO2produced by in situ remineralization.

114C-DIC signatures, which are much more14C-depleted in the case of carbonate weathering (Fig. 12).

Radiocarbon data on DIC from our survey (Table 2, Fig. 12) vary from contemporary values upstream of Masinga reservoir to very depleted (i.e. old) values further down-stream, and highly depleted values in one of the tribu-taries draining Mt. Kenya (−658‰) and in the Tana Delta (−552‰). The latter two values are even lower then would be expected based on carbonate dissolution by biogeonic CO2(i.e., intermediate between14C-free carbonates and or-ganic matter), and alternative DIC sources must therefore be invoked. Two potential sources include (i) metamorphic CO2, which is a plausible source in volcanic areas such as the Mt. Kenya tributary, (e.g., see Evans et al. (2008) and Gaillarded and Galy (2008)), and (ii) direct carbonate disso-lution by organic or sulfuric acids. The latter would appear the most likely explanation for the14C-depleted DIC signa-ture observed in the Tana delta.

For the main Tana River, the 114CDICvalues are relatively low compared to data from most other large river basins (e.g., Mayorga et al., 2005), but similarly low 114CDICdata have been reported from the Strickland river (Papua New Guinea, see Alin et al., 2007) and are more typical of higer-altitude streams (see references in Alin et al., 2007) due to e.g. con-tributions by carbonate weathering or groundwater contri-butions. In-stream production of DIC along this stretch of the river does not appear to be significant in the overall DIC transported downstream: the DIC inputs from respiration are expected to similar to those of POC (δ13C∼ −22‰, 114C between −40 and −120‰) which would result in an op-posite downstream trend as that observed (Table 2). Our combined δ13C and 114C data thus suggest that alkalinity in the Tana headwater streams results from a variable combi-nation of both silicate and carbonate weathering inputs, and

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2488 S. Bouillon et al.: A dry season basin-scale survey from headwaters to the delta

stress the role of these processes in setting baseline δ13CDIC across a range of settings. Finally, an important implication for these low 114CDICvalues for future radiocarbon studies in this system is that in-situ primary production in the lower Tana River will also be characterized by low 114CPOC val-ues, i.e. that recent phytoplankton production is likely to have an “old”14C age.

4.4 Methane

Methane concentrations were highly variable, ranging be-tween 25 and 505 nM, and always highly oversaturated (850– 21 700%), in accordance with data from other temperate and tropical streams and rivers (e.g., Jones and Mulholland, 1998; Middelburg et al., 2002; Abril et al., 2005, 2007; Gu´erin et al., 2006 and references therein). CH4 concen-trations in rivers result from the balance between inputs from groundwaters followed by transport with water masses, pro-duction in river sediments, and losses due to oxidation in waters and surface sediments and to the outgassing to the atmosphere. The relatively low (below 100 nM) CH4 con-centrations in the low-order tributaries of the Tana River, at high and intermediate elevations, suggest that soil CH4 in-puts were moderate in this area at that season. In some US temperate rivers, Jones and Mulholland (1998) have found a CH4maximum in small headwater streams at highest eleva-tion, but also at highest organic soil content, they attributed to large CH4groundwater inputs from soils. This trend does not appear in the tributaries of the Tana River. Along the main course of the Tana River, CH4concentrations were also relatively low (around or below 100 nM), with the excep-tion of the vicinity of the Masinga reservoir and in the delta (Fig. 4b). Such generally low CH4 concentrations suggest moderate production in the river itself, in comparison with other rivers, where CH4maxima where found during low dis-charge periods (De Angelis and Lilley, 1987; De Angelis and Scranton, 1993; Abril et al., 2007).

Hydroelectric reservoirs have been shown to be substantial sources of CH4emission to the atmosphere (St. Louis et al., 2000). Our data from Masinga reservoir show relatively high CH4 concentrations in the inflowing Tana River (505 nM) and in the outflow of the reservoir (372 nM), but much lower concentrations in the upper water column (51±7 nM). High concentration at the entrance of the reservoir is probably due to intense local sedimentation in this area where water cur-rent decreases. High sedimentation promotes methane pro-duction and diffusion in the water column, which is likely still well mixed in this area. High methane production prob-ably occurs also in the deeper reservoir, but as the water col-umn appears stratified, it affects only the deeper, anoxic wa-ters. The lower concentrations in surface waters are most likely the result of high oxidation rates of methane diffusing from anoxic bottom waters into the oxic upper water layer, as reported in other tropical reservoirs (e.g., Gu´erin and Abril, 2007). The relatively high CH4concentrations at the outflow

of the reservoir is due to the deep location of the outlet where CH4-rich anoxic water are passing. Part of the CH4escapes to the atmosphere immediately downstream of the dam due pressure change and high turbulence, while further degassing may occur downstream in the river (Gu´erin et al., 2006). CH4 concentrations further downstream are much lower (Fig. 4b), consistent with important further CH4degassing and/or ox-idation within the river. Towards the Tana Delta, however, an increase in CH4concentrations is observed with highest concentrations in the most downstream site (387 nM), which suggests increased lateral or sediment CH4inputs in the delta wetlands.

4.5 Importance of internal sediment storage and resus-pension

The most striking pattern in the suspended matter data is the gradual but steep increase in TSM observed along the middle and lower course of the main Tana River, from low values of 15.2 and 12.2 mg L−1before and after Masinga reservoir, re-spectively, to 483 mg L−1in the most downstream sampling station (Fig. 6). As sampling was conducted during the dry season, no more tributary inputs reach the Tana River below the Nyambene Hills tributaries (Fig. 1), suggesting that the main part of this increase in TSM is caused by resuspension of internally stored sediment. In various other tropical river systems, sediment delivery is observed to be highly episodic or concentrated in short-term periods with highest precipita-tion (e.g., Townsend-Small et al., 2007, Hilton et al., 2008). According to Dunne (1979), 35–75% of sediment delivery to Kenyan river systems is thought to occur during periods when water flow is in the highest 1% range of flow rates, depending on the dominant land use in the catchments (e.g., with a much higher fraction of sediment delivery during such events for grazing lands compared to forest-dominated catch-ments). With this in mind, substantial within-channel sed-iment storage appears highly likely. Kitheka et al. (2005) provide some data on the seasonality of discharge and TSM concentrations at Garsen (corresponding to our sampling sta-tion 24) and found that peak TSM concentrasta-tions typically preceded discharge peaks – suggesting the release of rela-tively mobile sediment during the first stages of river dis-charge increases. The latter is consistent with observations in other large river systems such as the Amazon, Missis-sippi and Orinoco where a seasonal cycle of sediment stor-age and resuspension has been observed (Meade et al., 1985; Meade, 1988; Mossa, 1996). Along a 900 km transect of the lower Mississippi, for example, Mossa (1996) observed both downstream increases and decreases of TSM levels depend-ing on river discharge stage. The deposition/resuspension cy-cles in large river networks appear to be governed mainly by seasonal changes in river discharge and river slope (Meade, 1988), but the presence of floodplains allowing temporal de-position and retention also play a role. To our knowledge, the ∼30-fold downstream increase in TSM concentrations

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observed along the Tana River during our sampling period is much more pronounced than that observed in the mainstem of any other river system so far. Seasonal altitudinal profiles of TSM concentrations during different stages of river dis-charge will be required to further document deposition and resuspension cycles in this river system, and its consequences for C and nutrient cycling.

An important implication of such pronounced resuspen-sion events is that much of the suspended matter observed in the lower Tana River has likely experienced a much longer residence time within the river system compared to the (smaller) pool of TSM in the higher reaches of the Tana River, i.e. the gradient in TSM concentrations is expected to coincide with a gradient of lower to higher residence time within the system. The longer residence time creates op-portunities for biogeochemical processing of the associated organic matter (Battin et al., 2008) which become evident when comparing the observed biogeochemical characteris-tics of particulate OC between the upper and lower Tana River (see below).

4.6 Organic matter changes along the river continuum Riverine carbon is either produced within or delivered to the river. The contribution of phytoplankton production to stock of POC can be estimated from C/chl-a ratios. The observed ratios in the river Tana and its tributaries are much higher than those typically found in phytoplankton (>500; Fig. 11b, typical ratios for phytoplankton ∼50), implying that more than 90% of the particulate organic carbon is detrital. Soil organic carbon content appeared to be an important factor influencing riverine %POC/TSM for the tributaries (data not shown), but the latter were consistently higher than soil %OC (top 5 cm), indicating that suspended particulate organic car-bon was also derived from direct litter inputs and/or from top-soil layers, where %OC is likely higher than in the top 5 cm profile which was sampled here. Similarly, δ13CPOC signa-tures in the 11 tributary streams were significantly correlated to those in soil organic matter (p=0.02, data not shown), but the δ13C range was much narrower in suspended matter (−26.5 to −22.7‰) than in soils (−26.5 to −13.2‰). The latter pattern is not unexpected given that soil δ13C values in these subcatchments (which all appear to have mixed C3 and C4 vegetation) are heterogeneous and vary spatially depend-ing on the dominant vegetation, resultdepend-ing in an ‘averaged’ mixed δ13C signature in riverine suspended matter.

The strong downstream increase in TSM concentrations along the main Tana River (Fig. 6a) coincides with a strong increase in POC (Fig. 6b), but the latter is less pronounced, as a result, %POC/TSM decreased from 4.6% below Masinga reservoir to ∼1.1% in the most downstream sampling sta-tions (Fig. 7). Given that the increase in TSM concentra-tions can be linked to resuspension of internally stored sed-iment (see above), this significant decrease in %POC/TSM can be interpreted as an important loss of mineral-associated

organic carbon during particle residence within the river sys-tem. If we assume that the original %POC/TSM during the time of sediment delivery to the river system is similar to that observed in TSM in the upper Tana River, we estimate that

∼75% of particle-associated organic carbon was remineral-ized during its riverine transit. This estimate should be con-sidered as very preliminary, since future seasonal data are are required to confirm our assumption that %POC/TSM of sed-iment inputs during high sedsed-iment influx events are similar to those observed upstream here during the dry season.

The specific surface areas measured on five of the Tana River TSM samples from the lower river are very high (63.6–82.2 m2g−1) compared to values reported for coastal sediments, estuaries and rivers (typically <50 m2g−1), and OC:SA ratios found here (0.16–0.22 mg C m−2) are conse-quently in the lower range of those reported in the literature (e.g., Keil et al., 1997; Aufdenkampe et al., 2007). The SA values in TSM are also consistently higher than those ob-served in surface soils (<63 µm fraction) which ranged be-tween 11.8 and 67.7 m2g−1 (data not shown). Soil OC:SA ratios (0.12 to 3.76 mg C m−2, one exceptionally high value of 13.6 mg C m−2) were highly variable and generally higher those of riverine particles (0.220 to 0.143 mg C m−2), in-dicating that riverine particles have been subjected to ex-tensive degradation losses. Moreover, the downstream de-crease in %POC/TSM observed in the main Tana River ap-pears, based on the few SA measurements made on these TSM samples, to match also with a decreased surface load-ing of organic carbon on these particles (OC:SA from 0.220 to 0.143 mg C m−2between station 20 and 24).

δ13CPOC signatures below Masinga reservoir are 13 C-depleted (−25.2‰) relative to those observed upstream of the reservoir (−22.8‰, Fig. 9). In combination with the low δ13C signatures in Masinga reservoir surface waters (−29.0±0.3‰), which appear to are dominated by phy-toplankton biomass (based on the low POC:chl-a ratios, Fig. 11b), suggest that part of the POC export from Masinga reservoir is derived from phytoplankton production in the reservoir. The subsequent downstream sampling site on the Tana River, however, shows a distinctly higher δ13CPOC (−21.5‰, i.e., a shift of 3.7‰) and a large concurrent de-crease in %POC/TSM (from 4.6 to 2.0%). The combination of these data allow us to estimate the expected δ13C signa-ture of the POC lost in this section of the river at ∼−28.0‰. This signature suggests that the13C-depleted fraction (which likely consists of phytoplankton biomass from the reservoir) was rapidly and preferentially degraded, consistent with ear-lier observations in other tropical reservoirs (De Junet et al., 2009). Further downstream, δ13CPOC shows relatively mi-nor variations (−22.9 to −22.2‰) until the most downstream station in the Tana delta where δ13CPOCincreases (−21.2‰). Since marine inputs can be excluded in the freswhater part of the delta, the latter trend could suggest an increased contri-bution of local C4 material (which would be consistent also with the slight increase in %POC/TSM). In contrast to the

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2490 S. Bouillon et al.: A dry season basin-scale survey from headwaters to the delta

marked changes in the composition of POC before and af-ter Masinga reservoir, DOC concentrations and δ13C signa-tures are markedly uniform between the Tana River before and after the reservoir, and in surface waters of Masinga reservoir. None of the δ13CPOC variations along the Tana River between Meru and Garsen (Fig. 1) are correlated with changes in %POC/TSM; interpreted in the context of pro-gressive degradation of POC, this suggest that little selectiv-ity in remineralization of C3 and C4-derived carbon occurs.

Radiocarbon data on POC (114CPOC), available for lim-ited number of sites along the Tana River, ranged between

−116 and −35‰ (i.e., 14C age of ∼935 to ∼230 yr). Ray-mond and Bauer (2001) were among the first to demonstrate that rivers may deliver relativey old,14C-depleted POC to the coastal zone, while DOC is often younger in age. Both exper-imental work (e.g., Raymond and Bauer, 2001) and field data (e.g., McCallister et al., 2004; Mayorga et al., 2005) have suggested that intensive bacterial remineralization can occur selectively, and hence substantially alter the age and compo-sition of organic ultimately exported. In our dataset, there is a general decrease in 114CPOCalong the lower Tana River, which coincides with the overall decrease in %POC/TSM (Fig. 10). Interpreting the gradual decrease in %POC/TSM in terms of remineralization of POC during the residence period of particles within the river system, this decrease in 14C age of associated POC indicates selective remineraliza-tion of a modern POC fracremineraliza-tion (estimated 114C of +56 to +140‰, depending on whether or not the data from station 11 are included in the regression used), imprinting the resid-ual carbon delivered to the estuary and delta with an old, 14C-depleted signature. Alternatively, within river primary production would add14C-old organic carbon because of the very low 114CDIC numbers (Table 2), but this freshly pro-duced material is likely readily remineralised and will thus not contribute to POC pools.

DOC concentrations ranged between 0.3 and 2.5 mg L−1, with the majority of data in a fairly narrow range between 0.6 and 1.2 mg L−1(Fig. 8a). DOC was the largest organic carbon pool in high altitude tributaries (DOC/POC ratios of 1.9±0.2, Fig. 8b) while POC dominated in tributaries draining Mt. Kenya and Nyambene Hills (DOC/POC ratios of 0.8±0.3). Along the main Tana River, DOC concentra-tions varied within a very narrow range (0.98±0.14 mg L−1, Fig. 8a), contrasting sharply with the steep downstream in-crease in POC concentrations (Fig. 6b). DOC concentrations in the lower Tana River are markedly lower than those ob-served in other large African rivers such as the Congo, Nile, Gambia and Niger (Martins and Probst, 1991), but consis-tent with average values for semi-arid climates presented in Spitzy and Leenheer (1991). As a result of the contrast in DOC and POC concentration profiles, DOC/POC ratios de-clined from ∼1.6 in the vicinity of Masinga reservoir to 0.2 along the lower Tana River (Fig. 8b), and were inversely re-lated to logarithm of TSM concentrations (Fig. 8c). An in-verse relationship between log(TSM) and DOC/POC ratios

has been observed in a wide range of river systems and es-tuaries (e.g., Ittekkot and Laane, 1991; Abril et al., 2002; Middelburg and Herman, 2008; Ralison et al., 2008). When comparing our data from headwater streams, the main Tana River, and data from the freshwater part of the Tana estuary (Bouillon et al., 2007, Fig. 8c), however, different patterns in the DOC/POC versus log(TSM) relationship can be dis-cerned. While the slope of the relationships appear fairly similar, DOC/POC ratios are lower in the headwater streams compared to the main river for similar TSM values, and DOC/POC ratios from the freshwater estuary are higher than those found here on the main Tana River (Fig. 8c).

The DOC/POC ratios in the most downstream stations are markedly lower than those observed in the freshwater and oligohaline part of the estuary (1.4±1.3, Bouillon et al., 2007), suggesting either pronounced seasonal variations or substantial additional lateral DOC inputs in the upper tidal range of the river. δ13CDOCalong the Tana River varied lit-tle (overall range between −24.0 and −22.7‰), and in con-trast to POC, did not show a marked depletion in 13C ei-ther in surface waters of Masinga reservoir (−23.9±0.3‰) or at the outflow of the reservoir (−23.9‰). Thus, in con-trast to POC, phytoplankton production in Masinga reservoir surface waters appeared to have little impact on surface wa-ter δ13CDOC. This suggests that either little excretion of DOC occurs during primary production in this system, or that la-bile algae-derived DOC is rapidly remineralized or photo-oxidized in the reservoirs surface waters, with little net effect on overall DOC concentrations and δ13C signatures. Overall,

δ13CDOC and δ13CPOC were clearly uncoupled and showed a relatively weak relationship (Fig. 9c), suggesting that de-spite clear evidence for partitioning of OC between POC and DOC (i.e., the relationships between DOC/POC and TSM described above), a large fraction of the POC pool does not readily or dynamically exchange with dissolved C pools.

Acknowledgements. We thank Pieter van Rijswijk, Peter van

Breugel, and Marco Houtekamer (NIOO-CEME), Jacques Navez (KMMA, Tervuren), Mathieu Boudin (KIK, Brussels), Dominique Poirier (EPOC, Bordeaux), and Xiaomei Xu (UC Irvine) for analyt-ical assistance. St´ephanie Duvail and Olivier Hamerlynck provided stimulating discussions, Gabriel Kung` u provided excellent company and assistance in the field, and David P. Gillikin provided useful comments on a draft version of this ms. Two anonymous referees provided excellent and constructive comments on the original version of this manuscript. This research was supported by the FWO-Vlaanderen (contracts G.0632.06, G.0395.07, and travel grant to S.B.), and by the Netherlands Organisation for Scientific Research (PIONIER). This is publication 4646 of the Netherlands Institute of Ecology (NIOO-KNAW).

Figure

Fig. 1. Location of the Tana River basin and sampling locations. Black symbols: main Tana River; open symbols: Masinga reservoir; grey symbols: tributaries.
Table 1. Overview of sampling locations and selected water chemistry characteristics. Note that the full data are available as an electronic supplementary file.
Fig. 2. Profile of total alkalinity (TA) in headwater streams, Masinga reservoir, and along the main Tana River
Fig. 3. (a) Profile of δ 13 C DIC in headwater streams, Masinga reservoir, and along the main Tana River, and (b) plot of DIC concentrations versus δ 13 C DIC .
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